Readiness Score API: POST /api/audit Full Reference

The Readiness Score API inspects a domain across five capability areas — discoverability, catalog, checkout, schema, and attribution — and returns a single score and a prioritised list of gaps to fix. Use it to assess a domain before implementation begins, to validate after each implementation step, or to run batch audits across multiple client domains. All calls require authentication — see Authentication.

Endpoint

POST https://asva-ai.com/api/audit

Request parameters

string

required

The domain to audit, without https://. Example: "yourstore.com"

string[]

Specific checks to run. Omit this field to run all checks.Available values: well_known, catalog, checkout, schema, feed, attribution, entity

boolean

When true, the API returns a cached result without re-fetching the domain. Use this during development to test your integration without triggering a live audit.

What each check tests:

Check	What it tests
`well_known`	`/.well-known/ucp` presence, validity, and accessibility
`catalog`	Product catalog endpoint structure and data quality
`checkout`	UCP/ACP checkout endpoint availability
`schema`	JSON-LD `Product`, `Offer`, `Organization` schema on product pages
`feed`	Google Merchant Center feed quality
`attribution`	Asva attribution snippet presence
`entity`	Entity consistency — brand name and organization schema

Example request:

{
  "domain": "yourstore.com",
  "checks": ["well_known", "catalog", "checkout", "schema", "attribution"],
  "dry_run": false
}

Response fields

string

The domain that was audited.

integer

Overall readiness score from 0 to 100. Higher is better.

string

Letter grade based on the score.

Grade	Score range
A	80–100
B	60–79
C	40–59
D	0–39

string

ISO 8601 timestamp of when the audit ran.

array

Issues found, ordered by severity. Each item in the array contains:

string

Unique identifier for this gap type, for example well_known_missing.

string

Which check category this gap belongs to.

string

How urgently this gap needs fixing: critical, high, medium, or low.

string

Short human-readable description of the gap.

string

Full explanation of the gap and its impact on AI commerce.

string

Link to the relevant Asva tool to fix this gap. May be null if no tool applies.

object

Score breakdown by category. Each field is an integer from 0 to 100.

integer

Score for agent discoverability — manifest presence and validity.

integer

Score for product catalog quality and structure.

integer

Score for checkout endpoint availability and correctness.

integer

Score for attribution snippet presence and configuration.

string[]

List of check IDs that passed with no issues.

Severity reference

Severity	Meaning
`critical`	Blocks agent discovery or checkout. Fix immediately.
`high`	Significantly reduces AI traffic or conversion. Fix soon.
`medium`	Affects attribution or discoverability but not checkout.
`low`	Minor improvement opportunity.

Example request and response

curl -X POST https://asva-ai.com/api/audit \
  -H "Authorization: Bearer $ASVA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "domain": "yourstore.com"
  }'

const response = await fetch('https://asva-ai.com/api/audit', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${process.env.ASVA_API_KEY}`,
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({ domain: 'yourstore.com' })
})

const audit = await response.json()
console.log(`Score: ${audit.score} (${audit.grade})`)
console.log('Critical gaps:', audit.gaps.filter(g => g.severity === 'critical'))

import requests

r = requests.post(
    'https://asva-ai.com/api/audit',
    headers={'Authorization': f'Bearer {ASVA_API_KEY}'},
    json={'domain': 'yourstore.com'}
)
audit = r.json()
print(f"Score: {audit['score']} ({audit['grade']})")

Example response:

{
  "domain": "yourstore.com",
  "score": 42,
  "grade": "C",
  "checked_at": "2026-04-10T11:00:00Z",
  "gaps": [
    {
      "id": "well_known_missing",
      "check": "well_known",
      "severity": "critical",
      "label": "/.well-known/ucp not found",
      "detail": "No response at https://yourstore.com/.well-known/ucp. Create this file to enable agent discovery.",
      "fix_url": "https://asva-ai.com/tools/manifest"
    },
    {
      "id": "product_schema_incomplete",
      "check": "schema",
      "severity": "high",
      "label": "Product JSON-LD schema missing on 6 pages",
      "detail": "Checked 10 product pages; 6 have no Product or Offer schema. AI systems cannot cite or price these products.",
      "fix_url": null
    },
    {
      "id": "dark_traffic_untracked",
      "check": "attribution",
      "severity": "medium",
      "label": "Asva attribution snippet not detected",
      "detail": "Install the Asva snippet to surface AI-sourced sessions in GA4.",
      "fix_url": "https://asva-ai.com/tools/readiness"
    }
  ],
  "breakdown": {
    "discoverability": 60,
    "catalog": 45,
    "checkout": 30,
    "attribution": 0
  },
  "passed": [
    "https_enabled",
    "feed_exists",
    "merchant_center_connected"
  ]
}

Batch auditing

For agencies auditing multiple domains, loop through the API:

#!/bin/bash
domains=("client1.com" "client2.com" "client3.com")

for domain in "${domains[@]}"; do
  result=$(curl -s -X POST https://asva-ai.com/api/audit \
    -H "Authorization: Bearer $ASVA_API_KEY" \
    -H "Content-Type: application/json" \
    -d "{\"domain\": \"$domain\"}")

  score=$(echo $result | jq '.score')
  grade=$(echo $result | jq -r '.grade')
  echo "$domain: $score ($grade)"
done

The /api/audit endpoint allows 60 requests per hour. Space out batch jobs or use dry_run: true for subsequent calls against the same domain within the same session.

Readiness Score tool — browser UI version of this API
Manifest API — generate a manifest to fix well_known_missing gaps
UCP Implementation — fix UCP gaps step by step

​Endpoint

​Request parameters

​Response fields

​Severity reference

​Example request and response

​Batch auditing

​Related

Endpoint

Request parameters

Response fields

Severity reference

Example request and response

Batch auditing

Related